1992Canadian Journal of Civil EngineeringRequires access

Use of Akaike information criterion for selection of flood frequency distribution

K. C. Ander Chow, W. E. Watt

Open publisher page 11 citations

Abstract

When conducting a conventional single-station flood frequency analysis, an appropriate distribution must be selected. Typically, sample statistics, probability plots, goodness-of-fit tests, etc. are used to facilitate the decision process. For the predominate case of a relatively short record length of flood series, this standard approach leads to undue emphasis on goodness of fit and virtually no consideration of the uncertainty due to additional parameters. The information criterion suggested by Akaike (AIC) is a measure to evaluate the "benefit" of goodness of fit and the "cost" of parameter uncertainty. The criterion is tested for 42 long-term hydrometric stations across Canada and its applicability and limitations are demonstrated in eight samples. The AIC is recommended as an aid in selecting a flood frequency distribution. Key words: flood frequency, goodness of fit, single station, information criterion.

About this research paper

What this paper is about

When conducting a conventional single-station flood frequency analysis, an appropriate distribution must be selected. Typically, sample statistics, probability plots, goodness-of-fit tests, etc. are used to facilitate the decision process. For the predominate case of a relatively short record length of flood series, this standard approach leads to undue emphasis on goodness of fit and virtually no consideration of the uncertainty due to additional parameters. The information criterion suggested by Akaike (AIC) is a measure to evaluate the "benefit" of goodness of fit and the "cost" of parameter uncertainty. The criterion is tested for 42 long-term hydrometric stations across Canada and its applicability and limitations are demonstrated in eight samples. The AIC is recommended as an aid in selecting a flood frequency distribution. Key words: flood frequency, goodness of fit, single station, information criterion.

Why it matters

OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

When conducting a conventional single-station flood frequency analysis, an appropriate distribution must be selected. Typically, sample statistics, probability plots, goodness-of-fit tests, etc. are used to facilitate the decision process. For the predominate case of a relatively short record length of flood series, this standard approach leads to undue emphasis on goodness of fit and virtually no consideration of the uncertainty due to additional parameters. The information criterion suggested by Akaike (AIC) is a measure to evaluate the "benefit" of goodness of fit and the "cost" of parameter uncertainty. The criterion is tested for 42 long-term hydrometric stations across Canada and its applicability and limitations are demonstrated in eight samples. The AIC is recommended as an aid in selecting a flood frequency distribution. Key words: flood frequency, goodness of fit, single station, information criterion.

Key concepts: Akaike information criterion, Goodness of fit, Statistics, Bayesian information criterion, Flood myth, Mathematics, Model selection, Frequency distribution

Related papers

Back to paper searchBrowse research topicsOriginal source
Use of Akaike information criterion for selection of flood frequency distribution — Research Paper | ScholarLens